Target recognition involves the analysis of two-dimensional images in order to identify targets. Many systems and methods incorporate a three-step process in which: (i) a very fast pre-screener is used to identify regions of interest or target candidates within an image; (ii) a slower intermediate discriminator evaluates each region of interest in more detail, further reducing the number of candidates; and (iii) finally the most careful process positively identifies targets a process which sometimes includes locating the most vulnerable spot within the target.
Two dimensional sensors such as video or Forward-Looking Infrared Sensors (FLIRS) are used to analyze a tremendous amount of incoming information in their search to correctly identify a potential target. With data refresh rates of thirty frames per second or higher, the target detection system must rapidly locate any targets observed by the sensor.
The first detection phase evaluates every pixel in the scene, and should avoid any errors of omission. Accordingly, during the first detection phase there will be many “false alarms.” One method used in this first phase is to find warm objects of about the same size as the expected target. This works very well with older FLIRS which were blind to the direct radiation from the sun. Only after the sunlight is turned into heat is it visible. Because of the fundamental resolution limitation of these wavelengths, practical FLIR apertures were between six and twelve inches in diameter.
In order to attain an image with a resolution sufficient to identify tactical targets with sensors carried by small diameter rockets or sub-munitions, the magnitude of the FLIRS aperture becomes the dominant design constraint. For diameter constrained applications using the shorter wavelength FLIR is the only solution.
Short wavelength FLIRS using traditional blob-finding algorithms for the pre-screener will have difficulty detecting a target because the scene will often be dominated by the reflected infrared energy from the sun, rather than the heat internally generated by the target itself. Infrared energy from the sunlight adds contrast detail in what would be uniform black background using the longer wavelength of the older FLIRS. In addition, sunlight adds contrast detail within the target. This change in wavelength to accommodate smaller diameter sensors will increase the number of regions that must be analyzed further, and include more “false alarms” in the pre-screener phase.
Subsequent detection phases are typically much slower, however, and drain substantial processing resources. The increased number of potential targets with shorter wavelength FLIRS using blob finding algorithms means the efficiency of the target detection system may be greatly reduced. In a worst case situation this diminished efficiency can mean that the system fails to detect a real target because it will be forced to drop frames to keep up with the data flow.